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DBMS > Google Cloud Datastore vs. IBM Db2 Event Store vs. Microsoft Azure SQL Database vs. TigerGraph

System Properties Comparison Google Cloud Datastore vs. IBM Db2 Event Store vs. Microsoft Azure SQL Database vs. TigerGraph

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDistributed Event Store optimized for Internet of Things use casesDatabase as a Service offering with high compatibility to Microsoft SQL ServerA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelDocument storeEvent Store
Time Series DBMS
Relational DBMSGraph DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.13
Rank#71  Overall
#12  Document stores
Score0.18
Rank#315  Overall
#2  Event Stores
#26  Time Series DBMS
Score72.95
Rank#16  Overall
#11  Relational DBMS
Score1.44
Rank#152  Overall
#14  Graph DBMS
Websitecloud.google.com/­datastorewww.ibm.com/­products/­db2-event-storeazure.microsoft.com/­en-us/­products/­azure-sql/­databasewww.tigergraph.com
Technical documentationcloud.google.com/­datastore/­docswww.ibm.com/­docs/­en/­db2-event-storedocs.microsoft.com/­en-us/­azure/­azure-sqldocs.tigergraph.com
DeveloperGoogleIBMMicrosoft
Initial release2008201720102017
Current release2.0V12
License infoCommercial or Open Sourcecommercialcommercial infofree developer edition availablecommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++C++C++
Server operating systemshostedLinux infoLinux, macOS, Windows for the developer additionhostedLinux
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyes, details hereyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonoyesno
Secondary indexesyesnoyes
SQL infoSupport of SQLSQL-like query language (GQL)yes infothrough the embedded Spark runtimeyesSQL-like query language (GSQL)
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
Server-side scripts infoStored proceduresusing Google App EngineyesTransact SQLyes
TriggersCallbacks using the Google Apps Enginenoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosActive-active shard replicationyes, with always 3 replicas available
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyesyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyesyes
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardfine grained access rights according to SQL-standardRole-based access control

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More resources
Google Cloud DatastoreIBM Db2 Event StoreMicrosoft Azure SQL Database infoformerly SQL AzureTigerGraph
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